共查询到20条相似文献，搜索用时 109 毫秒
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Background
The starlet sea anemone Nematostella vectensis is a diploblastic cnidarian that expresses a set of conserved genes for gut formation during its early development. During the last decade, the spatial distribution of many of these genes has been visualized with RNA hybridization or protein immunolocalization techniques. However, due to N. vectensis'' curved and changing morphology, quantification of these spatial data is problematic. A method is developed for two-dimensional gene expression quantification, which enables a numerical analysis and dynamic modeling of these spatial patterns.Methods/Result
In this work, first standardized gene expression profiles are generated from publicly available N. vectensis embryo images that display mRNA and/or protein distributions. Then, genes expressed during gut formation are clustered based on their expression profiles, and further grouped based on temporal appearance of their gene products in embryonic development. Representative expression profiles are manually selected from these clusters, and used as input for a simulation-based optimization scheme. This scheme iteratively fits simulated profiles to the selected profiles, leading to an optimized estimation of the model parameters. Finally, a preliminary gene regulatory network is derived from the optimized model parameters.Outlook
While the focus of this study is N. vectensis, the approach outlined here is suitable for inferring gene regulatory networks in the embryonic development of any animal, thus allowing to comparatively study gene regulation of gut formation in silico across various species. 相似文献7.
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Carlos Quijano Pavel Tomancak Jesus Lopez-Marti Mikita Suyama Peer Bork Marco Milan David Torrents Miguel Manzanares 《Genome biology》2008,9(12):R176
Background
The physical organization and chromosomal localization of genes within genomes is known to play an important role in their function. Most genes arise by duplication and move along the genome by random shuffling of DNA segments. Higher order structuring of the genome occurs in eukaryotes, where groups of physically linked genes are co-expressed. However, the contribution of gene duplication to gene order has not been analyzed in detail, as it is believed that co-expression due to recent duplicates would obscure other domains of co-expression.Results
We have catalogued ordered duplicated genes in Drosophila melanogaster, and found that one in five of all genes is organized as tandem arrays. Furthermore, among arrays that have been spatially conserved over longer periods than would be expected on the basis of random shuffling, a disproportionate number contain genes encoding developmental regulators. Using in situ gene expression data for more than half of the Drosophila genome, we find that genes in these conserved clusters are co-expressed to a much higher extent than other duplicated genes.Conclusions
These results reveal the existence of functional constraints in insects that retain copies of genes encoding developmental and regulatory proteins as neighbors, allowing their co-expression. This co-expression may be the result of shared cis-regulatory elements or a shared need for a specific chromatin structure. Our results highlight the association between genome architecture and the gene regulatory networks involved in the construction of the body plan. 相似文献10.
Background
The recent DREAM4 blind assessment provided a particularly realistic and challenging setting for network reverse engineering methods. The in silico part of DREAM4 solicited the inference of cycle-rich gene regulatory networks from heterogeneous, noisy expression data including time courses as well as knockout, knockdown and multifactorial perturbations.Methodology and Principal Findings
We inferred and parametrized simulation models based on Petri Nets with Fuzzy Logic (PNFL). This completely automated approach correctly reconstructed networks with cycles as well as oscillating network motifs. PNFL was evaluated as the best performer on DREAM4 in silico networks of size 10 with an area under the precision-recall curve (AUPR) of 81%. Besides topology, we inferred a range of additional mechanistic details with good reliability, e.g. distinguishing activation from inhibition as well as dependent from independent regulation. Our models also performed well on new experimental conditions such as double knockout mutations that were not included in the provided datasets.Conclusions
The inference of biological networks substantially benefits from methods that are expressive enough to deal with diverse datasets in a unified way. At the same time, overly complex approaches could generate multiple different models that explain the data equally well. PNFL appears to strike the balance between expressive power and complexity. This also applies to the intuitive representation of PNFL models combining a straightforward graphical notation with colloquial fuzzy parameters. 相似文献11.
Michael J. Monument Kirsten M. Johnson Elizabeth McIlvaine Lisa Abegglen W. Scott Watkins Lynn B. Jorde Richard B. Womer Natalie Beeler Laura Monovich Elizabeth R. Lawlor Julia A. Bridge Joshua D. Schiffman Mark D. Krailo R. Lor Randall Stephen L. Lessnick 《PloS one》2014,9(8)
Background
The genetics involved in Ewing sarcoma susceptibility and prognosis are poorly understood. EWS/FLI and related EWS/ETS chimeras upregulate numerous gene targets via promoter-based GGAA-microsatellite response elements. These microsatellites are highly polymorphic in humans, and preliminary evidence suggests EWS/FLI-mediated gene expression is highly dependent on the number of GGAA motifs within the microsatellite.Objectives
Here we sought to examine the polymorphic spectrum of a GGAA-microsatellite within the NR0B1 promoter (a critical EWS/FLI target) in primary Ewing sarcoma tumors, and characterize how this polymorphism influences gene expression and clinical outcomes.Results
A complex, bimodal pattern of EWS/FLI-mediated gene expression was observed across a wide range of GGAA motifs, with maximal expression observed in constructs containing 20–26 GGAA motifs. Relative to white European and African controls, the NR0B1 GGAA-microsatellite in tumor cells demonstrated a strong bias for haplotypes containing 21–25 GGAA motifs suggesting a relationship between microsatellite function and disease susceptibility. This selection bias was not a product of microsatellite instability in tumor samples, nor was there a correlation between NR0B1 GGAA-microsatellite polymorphisms and survival outcomes.Conclusions
These data suggest that GGAA-microsatellite polymorphisms observed in human populations modulate EWS/FLI-mediated gene expression and may influence disease susceptibility in Ewing sarcoma. 相似文献12.
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