Algorithm for spline-based elastic registration in application to confocal images of gene expression

Sorzano, Carlos Óscar S.; Blagov, Maxim; Thévenaz, P.; Myasnikova, Ekaterina; Samsonova, Maria; Unser, Michaël

doi:10.1134/s1054661806010299

Cited by 5 publications

(4 citation statements)

References 12 publications

(15 reference statements)

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“…The program of Sorzano et al 21 performs the elastic registration of segmentation gene expression patterns. This program deforms the coordinates non-linearly to make the images coincide as close as possible.…”

Section: Discussionmentioning

confidence: 99%

GCPReg package for registration of the segmentation gene expression data in Drosophila

Kozlov¹,

Myasnikova²,

Samsonova³

et al. 2009

Fly

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In modern functional genomics registration techniques are used to construct reference gene expression patterns and create a spatiotemporal atlas of the expression of all the genes in a network. In this paper we present a software package called GCPReg, which can be used to register the expression patterns of segmentation genes in the early Drosophila embryo. The key task, which this package performs, is the extraction of spatially localized characteristic features of expression patterns. To facilitate this task, we have developed an easy-to-use interactive graphical interface. We describe GCPReg usage and demonstrate how this package can be applied to register gene expression patterns in wild type and mutants. GCPReg has been designed to operate on a UNIX platform and is freely available via the Internet at http://urchin.spbcas.ru/downloads/GCPReg/GCPReg.htm.

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Section: Discussionmentioning

confidence: 99%

GCPReg package for registration of the segmentation gene expression data in Drosophila

Kozlov¹,

Myasnikova²,

Samsonova³

et al. 2009

Fly

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“…Recently a method for image registration based on a new strategy has been published. 30 This method, named as the algorithm for elastic registration deforms the coordinates non-linearly to make the images coincide as close as possible. After transformation all the registered images are brought to one and the same size.…”

Section: Discussionmentioning

confidence: 99%

Pipeline for acquisition of quantitative data on segmentation gene expression from confocal images

Surkova

Myasnikova²,

Janssens³

et al. 2008

Fly

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We describe a data pipeline developed to extract the quantitative data on segmentation gene expression from confocal images of gene expression patterns in Drosophila. The pipeline consists of five steps: image segmentation, background removal, temporal characterization of an embryo, data registration and data averaging. This pipeline was successfully applied to obtain quantitative gene expression data at cellular resolution in space and at the 6.5-minute resolution in time, as well as to construct a spatiotemporal atlas of segmentation gene expression. Each data pipeline step can be easily adapted to process a wide range of images of gene expression patterns. IntroductionBiology is increasingly asking quantitative questions. Quantification is essential to understand the principles of organism functioning. Modern physics and engineering provide tools and strategies for accurate measurements and the acquisition of comprehensive and consistent data sets. For example, microarrays are widely used to quantify the levels of gene expression, 1 and fluorescence restoration after photobleaching (FRAP) is applied to measure diffusion rate or molecular transport. 2 In the last decade developmental biology has achieved tremendous progress. Due to the success of genetics and functional genomics a large number of genes controlling development has been cloned and sequenced, the products of these genes have been identified, and the function of many of these molecules has been revealed. However, despite of these spectacular achievements the integrative picture of how an organism controls the phenotype of tissues and organs is still absent.The morphogenetic field is a basic unit of ontogeny. 3 This physically detached area is formed by complex coordinated interactions of transcripts and proteins that make up the field. Understanding the developmental processes within the morphogenetic field requires a quantitative characterization of the dynamics of each of the field components.Currently available methods for quantification of gene expression like microarrays, quantitative PCR and CAT assays have some limitations for investigations of developmental processes. All of these methods are based on the preparation of homogenates of cells and are unable to capture spatial information about gene expression.The study of development in morphogenetic fields requires methods for the acquisition of gene expression data that will allow monitoring the expression time course of all of the genes simultaneously at the resolution of a single cell. Confocal scanning microscopy of fluorescently tagged molecules constitute the most common data acquisition strategy, which preserves spatial information about the distribution of gene products. This method involves the recognition of protein or RNA in situ by target-specific primary antibodies or a labeled antisense RNA probe. The detection method is usually based on the use of secondary antibodies conjugated with a fluorophore. Confocal microscopy provides high quality digital images ready for computer pr...

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“…A procedure has recently been published for image registration that differs from what we developed (Sorzano et al, 2006). This method, called "elastic registration," elastically deforms images to overlap expression patterns in different embryos.…”

Section: Discussionmentioning

confidence: 99%

Methods for acquisition of quantitative data from confocal images of gene expression in situ

et al. 2008

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In this review, we summarize original methods for the extraction of quantitative information from confocal images of gene-expression patterns. These methods include image segmentation, the extraction of quantitative numerical data on gene expression, and the removal of background signal and spatial registration. Finally, it is possible to construct a spatiotemporal atlas of gene expression from individual images recorded at each developmental stage. Initially all methods were developed to extract quantitative numerical information from confocal images of segmentation gene expression in Drosophila melanogaster. The application of these methods to Drosophila images makes it possible to reveal new mechanisms in the formation of segmentation gene expression domains, as well as to construct a quantitative atlas of segmentation gene expression. Most image processing procedures can be easily adapted to process a wide range of biological images.

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Algorithm for spline-based elastic registration in application to confocal images of gene expression

Cited by 5 publications

References 12 publications

GCPReg package for registration of the segmentation gene expression data in Drosophila

GCPReg package for registration of the segmentation gene expression data in Drosophila

Pipeline for acquisition of quantitative data on segmentation gene expression from confocal images

Methods for acquisition of quantitative data from confocal images of gene expression in situ

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