Modeling the precision and robustness of Hunchback border during Drosophila embryonic development

Hardway, Heather; Mukhopadhyay, Bibhash; Burke, Thomas M.; Hitchman, Theron; Forman, Robin

doi:10.1016/j.jtbi.2008.05.021

Cited by 21 publications

(11 citation statements)

References 15 publications

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“…(87,88) These properties could dictate a robust network architecture, which involves redundancy at different levels and mechanisms for noise filtering. (89) For instance, establishment of very narrow, just one cell wide, engrailed and wingless expression stripes (segment polarity genes) requires interplay of both transcriptional gradients and cell-to-cell signaling. (90) Transcriptional pair-rule gradients (stripes) provide initial instructions, while intercellular Wingless and Hedgehog signaling refine segment polarity expression to cell-wide stripes.…”

Section: Gradients and Stripes In The Context Of Gene Networkmentioning

confidence: 99%

Stripe formation in the early fly embryo: principles, models, and networks

Papatsenko

2009

BioEssays

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Early development of animal embryos begins from spatially distributed products of gene expression, i.e., gradients. While maternal and early zygotic genes form broad and/or terminal gradients, their direct targets appear later on as relatively narrow stripes, which foreshadow presumptive germ layers or future segments. Evidently, stripe expression of the zygotic genes is among the key mechanisms of embryo patterning. In this paper, known qualitative and quantitative models for the stripe formation are considered on the example of early embryogenesis of Drosophila. The current model analysis emphasizes the role of spatial information flow in development. Discussion is given on frequent network motifs, pointing to spatial stripe formation solutions.

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Section: Gradients and Stripes In The Context Of Gene Networkmentioning

confidence: 99%

Stripe formation in the early fly embryo: principles, models, and networks

Papatsenko

2009

BioEssays

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“…Of all expression borders of Bcd gene targets that are formed with high precision, most attention was paid to the low variation in the posterior border of the anterior hb domain (Houchmandzadeh et al, 2002, 2005; Gregor et al, 2007a; Hardway et al, 2008; He et al, 2008) (Figs. 2e, 2f).…”

Section: Resultsmentioning

confidence: 99%

Study of stability mechanisms of embryonic development in fruit fly Drosophila

et al. 2011

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Living organisms well adapt themselves to changes in the environment and are robust to potential damage such as mutations. The epigenetic mechanism whereby the suppression of phenotypic variation is achieved has been called canalization. This paper summarizes results of research that employed experimental and theoretical approaches to uncover the mechanisms of canalization of variation in expression of segmentation genes.

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“…kinetic and transport) features which produce such robustness, another is to study how evolution might generate such robust GRNs. A number of workers [19, 20, 59] have started addressing this through the specific case of robustness of the hb gene product to variability in the maternal Bicoid (Bcd) transcription factor gradient. As shown in Fig.…”

Section: Evolutionary Computation Of Gene and Cell Regulatory Netwmentioning

confidence: 99%

“…Hardway et al [59] used a connectionist model of two gap genes ( hb and another factor) regulated by the Bcd gradient to study the selection for robustness. Using a variable Bcd input, they searched for conditions in which Hb displayed the experimentally observed precision.…”

Section: Evolutionary Computation Of Gene and Cell Regulatory Netwmentioning

confidence: 99%

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

Spirov

Holloway

2013

Methods

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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. Such work can generally be termed evolution in silico. Complementary to these biologically-focused approaches, a now well-established field of computer science is Evolutionary Computations (EC), in which highly efficient optimization techniques are inspired from evolutionary principles. In surveying biological simulation approaches, we discuss the considerations that must be taken with respect to: a) the precision and completeness of the data (e.g. are the simulations for very close matches to anatomical data, or are they for more general exploration of evolutionary principles); b) the level of detail to model (we proceed from ‘coarse-grained’ evolution of simple gene-gene interactions to ‘fine-grained’ evolution at the DNA sequence level); c) to what degree is it important to include the genome’s cellular context; and d) the efficiency of computation. With respect to the latter, we argue that developments in computer science EC offer the means to perform more complete simulation searches, and will lead to more comprehensive biological predictions.

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Modeling the precision and robustness of Hunchback border during Drosophila embryonic development

Cited by 21 publications

References 15 publications

Stripe formation in the early fly embryo: principles, models, and networks

Stripe formation in the early fly embryo: principles, models, and networks

Study of stability mechanisms of embryonic development in fruit fly Drosophila

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

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