Reconstruction of the Dynamics of Drosophila Genes Expression from Sets of Images Sharing a Common Pattern

Spirov, Alexander V.; Kazansky, Alexander B.; Timakin, Dmitry L.; Reinitz, John

doi:10.1006/rtim.2002.0292

Cited by 9 publications

(19 citation statements)

References 13 publications

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“…all DV dependence (e.g., for AP position along a stripe edge) removed. For details of the method, see Spirov et al (2002) and Spirov and Holloway (2003b).…”

Section: Ap Expression Profilesmentioning

confidence: 99%

Analysis of pattern precision shows that Drosophila segmentation develops substantial independence from gradients of maternal gene products

Holloway

Harrison

Kosman

et al. 2006

Developmental Dynamics

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We analyze the relation between maternal gradients and segmentation in Drosophila, by quantifying spatial precision in protein patterns. Segmentation is first seen in the striped expression patterns of the pair-rule genes, such as even-skipped (eve). We compare positional precision between Eve and the maternal gradients of Bicoid (Bcd) and Caudal (Cad) proteins, showing that Eve position could be initially specified by the maternal protein concentrations but that these do not have the precision to specify the mature striped pattern of Eve. By using spatial trends, we avoid possible complications in measuring single boundary precision (e.g., gap gene patterns) and can follow how precision changes in time. During nuclear cleavage cycles 13 and 14, we find that Eve becomes increasingly correlated with egg length, whereas Bcd does not. This finding suggests that the change in precision is part of a separation of segmentation from an absolute spatial measure, established by the maternal gradients, to one precise in relative (percent egg length) units.

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“…all DV dependence (e.g., for AP position along a stripe edge) removed. For details of the method, see Spirov et al (2002) and Spirov and Holloway (2003b).…”

Section: Ap Expression Profilesmentioning

confidence: 99%

Analysis of pattern precision shows that Drosophila segmentation develops substantial independence from gradients of maternal gene products

Holloway

Harrison

Kosman

et al. 2006

Developmental Dynamics

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“…Next, on a pairwise basis, we move (in 1D) the stripes into register along the AP axis, minimizing the variability in stripe spacing and overall expression domain. These two steps make for a tough optimization procedure, which is probably best solved with modern heuristic approaches such as GAs [6].…”

Section: Expression Pattern Variabilitymentioning

confidence: 99%

“…The y-coordinate remains the same while the x-coordinate is transformed as a function of both coordinates w and h (for details, see [6,15,16]). The parameters w 0 , h 0 , A, B, C, and D for each image are found by means of GAs.…”

Section: Deformations By Polynomial Seriesmentioning

confidence: 99%

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Evolutionary Techniques for Image Processing a Large Dataset of Early Drosophila Gene Expression

Spirov

Holloway

2003

EURASIP J. Adv. Signal Process.

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Understanding how genetic networks act in embryonic development requires a detailed and statistically significant dataset integrating diverse observational results. The fruit fly (Drosophila melanogaster) is used as a model organism for studying developmental genetics. In recent years, several laboratories have systematically gathered confocal microscopy images of patterns of activity (expression) for genes governing early Drosophila development. Due to both the high variability between fruit fly embryos and diverse sources of observational errors, some new nontrivial procedures for processing and integrating the raw observations are required. Here we describe processing techniques based on genetic algorithms and discuss their efficacy in decreasing observational errors and illuminating the natural variability in gene expression patterns. The specific developmental problem studied is anteroposterior specification of the body plan.

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“…The closest work to ours is that of [12] who use spline and wavelet based registration techniques in 1D along the anterior-posterior axis of the Drosophila embryo . More recently they have considered a 2D version of the problem in order to register the lateral surface of an embryo which has been "flattened" before imaging [13]. Figure 1 gives an overview of our technique.…”

Section: Introductionmentioning

confidence: 98%

Registering Drosophila embryos at cellular resolution to build a quantitative 3D atlas of gene expression patterns and morphology

Fowlkes¹,

Hendriks

Keränen

et al. 2005

2005 IEEE Computational Systems Bioinformatics Conference - Workshops (CSBW'05)

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The Berkeley Drosophila Transcription Network Project is developing a suite of methods to convert volumetric data generated by confocal fluorescence microscopy into numerical, three dimensional representations of gene expression at cellular resolution. One key difficulty is that fluorescence microscopy can only capture expression levels for a few gene products in a given animal. We report on a method for registering 3D expression data from different Drosophila embryos stained for overlapping subsets of gene products in order to build a composite atlas, ultimately containing coexpression information for thousands of genes. Our techniques have also allowed the discovery of a complex pattern of cell density across the blastula that changes over time and may play a role in gastrulation.

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Reconstruction of the Dynamics of Drosophila Genes Expression from Sets of Images Sharing a Common Pattern

Cited by 9 publications

References 13 publications

Analysis of pattern precision shows that Drosophila segmentation develops substantial independence from gradients of maternal gene products

Analysis of pattern precision shows that Drosophila segmentation develops substantial independence from gradients of maternal gene products

Evolutionary Techniques for Image Processing a Large Dataset of Early Drosophila Gene Expression

Registering Drosophila embryos at cellular resolution to build a quantitative 3D atlas of gene expression patterns and morphology

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