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Spirov A.V.,Computer Science and CEWIT | Spirov A.V.,RAS Sechenov Institute of Evolutionary Physiology and Biochemistry | Zagriychuk E.A.,RAS Sechenov Institute of Evolutionary Physiology and Biochemistry | Holloway D.M.,British Columbia Institute of Technology
Parallel Processing Letters | Year: 2014

The co-evolution of species with their genomic parasites (transposons) is thought to be one of the primary ways of rewiring gene regulatory networks (GRNs). We develop a framework for conducting evolutionary computations (EC) using the transposon mechanism. We find that the selective pressure of transposons can speed evolutionary searches for solutions and lead to outgrowth of GRNs (through co-option of new genes to acquire insensitivity to the attacking transposons). We test the approach by finding GRNs which can solve a fundamental problem in developmental biology: how GRNs in early embryo development can robustly read maternal signaling gradients, despite continued attacks on the genome by transposons. We observed co-evolutionary oscillations in the abundance of particular GRNs and their transposons, reminiscent of predator-prey or hostparasite dynamics. © 2014 World Scientific Publishing Company. Source


Shlemov A.,Saint Petersburg State University | Golyandina N.,Saint Petersburg State University | Holloway D.,British Columbia Institute of Technology | Spirov A.,Computer Science and CEWIT | Spirov A.,RAS Sechenov Institute of Evolutionary Physiology and Biochemistry
BioMed Research International | Year: 2015

In recent years, with the development of automated microscopy technologies, the volume and complexity of image data on gene expression have increased tremendously. The only way to analyze quantitatively and comprehensively such biological data is by developing and applying new sophisticated mathematical approaches. Here, we present extensions of 2D singular spectrum analysis (2D-SSA) for application to 2D and 3D datasets of embryo images. These extensions, circular and shaped 2D-SSA, are applied to gene expression in the nuclear layer just under the surface of the Drosophila (fruit fly) embryo. We consider the commonly used cylindrical projection of the ellipsoidal Drosophila embryo. We demonstrate how circular and shaped versions of 2D-SSA help to decompose expression data into identifiable components (such as trend and noise), as well as separating signals from different genes. Detection and improvement of under- and overcorrection in multichannel imaging is addressed, as well as the extraction and analysis of 3D features in 3D gene expression patterns. © 2015 Alex Shlemov et al. Source


Spirov A.V.,Computer Science and CEWIT | Spirov A.V.,RAS Sechenov Institute of Evolutionary Physiology and Biochemistry | Holloway D.M.,British Columbia Institute of Technology
2012 IEEE Symposium on Computational Intelligence and Computational Biology, CIBCB 2012 | Year: 2012

We use in silico evolution to study the generation of gene regulatory structures. A particular area of interest in evolutionary development (evo-devo) is the correspondence between gene regulatory sequences on the DNA (cis-regulatory modules, CRMs) and the spatial expression of the genes. We use computation to investigate the incorporation of new CRMs into the genome. Simulations allow us to characterize different cases of CRM to spatial pattern correspondence. Many of these cases are seen in biological examples; our simulations indicate relative advantages of the different scenarios. We find that, in the absence of specific constraints on the CRM-pattern correspondence, CRMs controlling multiple spatial domains tend to evolve very quickly. Genes constrained to a one-to-one CRM-pattern domain correspondence evolve more slowly. Of these, systems in which pattern domains appear in a particular order in evolution, as in insect segmentation mechanisms, take the longest time in in silico evolutionary searches. For biological cases of this type, it is likely that other selective advantages outweigh the time costs. © 2012 IEEE. Source


Shlemov A.,Saint Petersburg State University | Golyandina N.,Saint Petersburg State University | Holloway D.,British Columbia Institute of Technology | Spirov A.,Computer Science and CEWIT | Spirov A.,RAS Sechenov Institute of Evolutionary Physiology and Biochemistry
BioMed Research International | Year: 2015

Recent progress in microscopy technologies, biological markers, and automated processing methods is making possible the development of gene expression atlases at cellular-level resolution over whole embryos. Raw data on gene expression is usually very noisy. This noise comes from both experimental (technical/methodological) and true biological sources (from stochastic biochemical processes). In addition, the cells or nuclei being imaged are irregularly arranged in 3D space. This makes the processing, extraction, and study of expression signals and intrinsic biological noise a serious challenge for 3D data, requiring new computational approaches. Here, we present a new approach for studying gene expression in nuclei located in a thick layer around a spherical surface. The method includes depth equalization on the sphere, flattening, interpolation to a regular grid, pattern extraction by Shaped 3D singular spectrum analysis (SSA), and interpolation back to original nuclear positions. The approach is demonstrated on several examples of gene expression in the zebrafish egg (a model system in vertebrate development). The method is tested on several different data geometries (e.g., nuclear positions) and different forms of gene expression patterns. Fully 3D datasets for developmental gene expression are becoming increasingly available; we discuss the prospects of applying 3D-SSA to data processing and analysis in this growing field. © 2015 Alex Shlemov et al. Source


Spirov A.V.,Computer Science and CEWIT | Spirov A.V.,RAS Sechenov Institute of Evolutionary Physiology and Biochemistry | Holloway D.M.,British Columbia Institute of Technology
Procedia Computer Science | Year: 2013

A central question in evolutionary biology concerns the transition between discrete numbers of units (e.g. vertebrate digits, arthropod segments). How do particular numbers of units, robust and characteristic for one species, evolve into another number for another species? Intermediate phases with a diversity of forms have long been theorized, but these leave little fossil or genomic data. We use evolutionary computations (EC) of a gene regulatory network (GRN) model to investigate how embryonic development is altered to create new forms. The trajectories are epochal and non-smooth, in accord with both the observed stability of species and the evolvability between forms. © 2013 The Authors. Published by Elsevier B.V. Source

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