Body plan evolvability: The role of variability in gene regulatory networks.

Recent computational modeling of early fruit fly () development has characterized the degree to which gene regulation networks can be robust to natural variability. In the first few hours of development, broad spatial gradients of maternally derived transcription factors activate embryonic gap genes. These gap patterns determine the subsequent segmented insect body plan through pair-rule gene expression.

Evolution of the RNA world: From signals to codes.

The accumulated material in evolutionary biology, greatly enhanced by the achievements of modern synthetic biology, allows us to envision certain key hypothetical stages of prebiotic (chemical) evolution. This is often understood as the further evolution in the RNA World towards the RNA-protein World. It is a path towards the emergence of translation and the genetic code (I), signaling pathways with signaling molecules (II), and the appearance of RNA-based components of future gene regulatory networks (III).

Problem of Domain/Building Block Preservation in the Evolution of Biological Macromolecules and Evolutionary Computation.

Structurally and functionally isolated domains in biological macromolecular evolution, both natural and artificial, are largely similar to "schemata", building blocks (BBs), in evolutionary computation (EC). The problem of preserving in subsequent evolutionary searches the already found domains / BBs is well known and quite relevant in biology as well as in EC. Both biology and EC are seeing parallel and independent development of several approaches to identifying and preserving previously identified domains / BBs.

Modeling SELEX for regulatory regions using Royal Road and Royal Staircase fitness functions.

The field of evolutionary algorithms (EAs) emerged in the area of computer science due to transfer of ideas from biology and developed independently for several decades, enriched with techniques from probability theory, complexity theory and optimization methods. In this paper, we consider some recent results form the EAs theory transferred back into biology. The well-known biotechnological procedure SELEX (Systematic Evolution of Ligands by EXponential enrichment) is viewed as an experimental implementation of an evolutionary algorithm.

Gene regulatory networks in Drosophila early embryonic development as a model for the study of the temporal identity of neuroblasts.

Genes belonging to the "gap" and "gap-like" family constitute the best-studied gene regulatory networks (GRNs) in Drosophila embryogenesis. Gap genes are a core of two subnetworks controlling embryonic segmentation: (hunchback, hb; Krüppel, Kr; giant, gt; and knirps, kni) and (hb; Kr; pou-domain, pdm; and, probably, castor, cas). Of particular interest is that (hb, Kr, pdm, cas) also specifies the temporal identity of stem cells, neuroblasts, in Drosophila neurogenesis.

[Evolutionary Stability of Gene Regulatory Networks That Define the Temporal Identity of Neuroblasts].

The ensemble of gap genes is one of the best studied and most conserved gene regulatory networks (GRNs). Gap genes, such as hunchback (hb), Krüppel (Kr), pou-domain (pdm; pdm1 and pdm2), and castor (cas) genes belong to the well-known families Ikaros (IKZF1/hb), Krüppel-like factor (KLF/Kr), POU domain (BRN1/pdm-1, BRN2/pdm-2), and Castor homologs (CASZ1/cas), which are present in all vertebrate genomes and code for site-specific transcription factors. Gap genes form a core of an embryonic segmentation control subnetwork and define the temporal identity of neuroblasts in Drosophila embryos.

Noise model estimation with application to gene expression.

Algorithms for the estimation of noise level and the detection of noise model are proposed. They are applied to gene expression data for embryos. The 2D data on gene expression and the extracted 1D profiles are considered.

Two-Exponential Models of Gene Expression Patterns for Noisy Experimental Data.

Spatial pattern formation of the primary anterior-posterior morphogenetic gradient of the transcription factor Bicoid (Bcd) has been studied experimentally and computationally for many years. Bcd specifies positional information for the downstream segmentation genes, affecting the fly body plan. More recently, a number of researchers have focused on the patterning dynamics of the underlying bcd messenger RNA (mRNA) gradient, which is translated into Bcd protein.

Correction: Cortical movement of Bicoid in early Drosophila embryos is actin- and microtubule-dependent and disagrees with the SDD diffusion model.

[This corrects the article DOI: 10.1371/journal.pone.

Relative sensitivity analysis of the predictive properties of sloppy models.

Commonly among the model parameters characterizing complex biological systems are those that do not significantly influence the quality of the fit to experimental data, so-called "sloppy" parameters. The sloppiness can be mathematically expressed through saturating response functions (Hill's, sigmoid) thereby embodying biological mechanisms responsible for the system robustness to external perturbations. However, if a sloppy model is used for the prediction of the system behavior at the altered input (e.

Robustness of expression pattern formation due to dynamic equilibrium in gap gene system of an early Drosophila embryo.

The first manifestation of a segmentation pattern in the early Drosophila development is the formation of expression domains of genes belonging to the gap class. In our previous research the phenomenon of the gap system's robustness, exhibited as the ability to reduce highly variable gene expression in the course of development, was explained as a result of gene cross-regulation. In this paper we formulate the rigorous robustness conditions using the inherent properties of gap gene family.

Cortical movement of Bicoid in early Drosophila embryos is actin- and microtubule-dependent and disagrees with the SDD diffusion model.

The Bicoid (Bcd) protein gradient in Drosophila serves as a paradigm for gradient formation in textbooks. The SDD model (synthesis, diffusion, degradation) was proposed to explain the formation of the gradient. The SDD model states that the bcd mRNA is located at the anterior pole of the embryo at all times and serves a source for translation of the Bicoid protein, coupled with diffusion and uniform degradation throughout the embryo.

Transcriptional bursting in Drosophila development: Stochastic dynamics of eve stripe 2 expression.

Anterior-posterior (AP) body segmentation of the fruit fly (Drosophila) is first seen in the 7-stripe spatial expression patterns of the pair-rule genes, which regulate downstream genes determining specific segment identities. Regulation of pair-rule expression has been extensively studied for the even-skipped (eve) gene. Recent live imaging, of a reporter for the 2nd eve stripe, has demonstrated the stochastic nature of this process, with 'bursts' in the number of RNA transcripts being made over time.

Shaped 3D singular spectrum analysis for quantifying gene expression, with application to the early zebrafish embryo.

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).

Shaped singular spectrum analysis for quantifying gene expression, with application to the early Drosophila embryo.

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.

Mid-embryo patterning and precision in Drosophila segmentation: Krüppel dual regulation of hunchback.

In early development, genes are expressed in spatial patterns which later define cellular identities and tissue locations. The mechanisms of such pattern formation have been studied extensively in early Drosophila (fruit fly) embryos. The gap gene hunchback (hb) is one of the earliest genes to be expressed in anterior-posterior (AP) body segmentation.

Forced evolution by artificial transposons and their genetic operators: The ant navigation problem.

Modern evolutionary computation utilizes heuristic optimizations based upon concepts borrowed from the Darwinian theory of natural selection. Their demonstrated efficacy has reawakened an interest in other aspects of contemporary biology as an inspiration for new algorithms. However, amongst the many excellent candidates for study, contemporary models of biological macroevolution attract special attention.

Evolutionary Design of Gene Networks: Forced Evolution by Genomic Parasites.

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).

In silico evolution of the hunchback gene indicates redundancy in cis-regulatory organization and spatial gene expression.

Biological development depends on the coordinated expression of genes in time and space. Developmental genes have extensive cis-regulatory regions which control their expression. These regions are organized in a modular manner, with different modules controlling expression at different times and locations.

Using evolutionary computations to understand the design and evolution of gene and cell regulatory networks.

This paper surveys modeling approaches for studying the evolution of gene regulatory networks (GRNs). Modeling of the design or 'wiring' of GRNs has become increasingly common in developmental and medical biology, as a means of quantifying gene-gene interactions, the response to perturbations, and the overall dynamic motifs of networks. Drawing from developments in GRN 'design' modeling, a number of groups are now using simulations to study how GRNs evolve, both for comparative genomics and to uncover general principles of evolutionary processes.