Sequence context affects the rate of short insertions and deletions in flies and primates

Analysis of a large collection of short insertions and deletions in primates and flies shows that the rate of insertions or deletions of specific lengths can vary by more than 100 fold, depending on the surrounding sequence

Shake It, Don’t Break It: Positive Feedback and the Evolution of Oscillator Design

In cell cycle control, a negative feedback oscillator design is shown to be reinforced with a positive feedback loop, giving a robust oscillatory architecture that is surprisingly common in biology

Conservation of regulatory elements between two species of Drosophila

BACKGROUND: One of the important goals in the post-genomic era is to determine the regulatory elements within the non-coding DNA of a given organism's genome. The identification of functional cis-regulatory modules has proven difficult since the component factor binding sites are small and the rules governing their arrangement are poorly understood. However, the genomes of suitably diverged species help to predict regulatory elements based on the generally accepted assumption that conserved blocks of genomic sequence are likely to be functional. To judge the efficacy of strategies that prefilter by sequence conservation it is important to know to what extent the converse assumption holds, namely that functional elements common to both species will fall within these conserved blocks. The recently completed sequence of a second Drosophila species provides an opportunity to test this assumption for one of the experimentally best studied regulatory networks in multicellular organisms, the body patterning of the fly embryo. RESULTS: We find that 50%–70% of known binding sites reside in conserved sequence blocks, but these percentages are not greatly enriched over what is expected by chance. Finally, a computational genome-wide search in both species for regulatory modules based on clusters of binding sites suggests that genes central to the regulatory network are consistently recovered. CONCLUSIONS: Our results indicate that binding sites remain clustered for these "core modules" while not necessarily residing in conserved blocks. This is an important clue as to how regulatory information is encoded in the genome and how modules evolve

Computational detection of genomic cis-regulatory modules applied to body patterning in the early Drosophila embryo

BACKGROUND: Regulation of gene transcription is crucial for the function and development of all organisms. While gene prediction programs that identify protein coding sequence are used with remarkable success in the annotation of genomes, the development of computational methods to analyze noncoding regions and to delineate transcriptional control elements is still in its infancy. RESULTS: Here we present novel algorithms to detect cis-regulatory modules through genome wide scans for clusters of transcription factor binding sites using three levels of prior information. When binding sites for the factors are known, our statistical segmentation algorithm, Ahab, yields about 150 putative gap gene regulated modules, with no adjustable parameters other than a window size. If one or more related modules are known, but no binding sites, repeated motifs can be found by a customized Gibbs sampler and input to Ahab, to predict genes with similar regulation. Finally using only the genome, we developed a third algorithm, Argos, that counts and scores clusters of overrepresented motifs in a window of sequence. Argos recovers many of the known modules, upstream of the segmentation genes, with no training data. CONCLUSIONS: We have demonstrated, in the case of body patterning in the Drosophila embryo, that our algorithms allow the genome-wide identification of regulatory modules. We believe that Ahab overcomes many problems of recent approaches and we estimated the false positive rate to be about 50%. Argos is the first successful attempt to predict regulatory modules using only the genome without training data. Complete results and module predictions across the Drosophila genome are available at http://uqbar.rockefeller.edu/~siggia/

Self-organization of stem cells into embryos: A window on early mammalian development.

Embryonic development is orchestrated by robust and complex regulatory mechanisms acting at different scales of organization. In vivo studies are particularly challenging for mammals after implantation, owing to the small size and inaccessibility of the embryo. The generation of stem cell models of the embryo represents a powerful system with which to dissect this complexity. Control of geometry, modulation of the physical environment, and priming with chemical signals reveal the intrinsic capacity of embryonic stem cells to make patterns. Adding the stem cells for the extraembryonic lineages generates three-dimensional models that are more autonomous from the environment and recapitulate many features of the pre- and postimplantation mouse embryo, including gastrulation. Here, we review the principles of self-organization and how they set cells in motion to create an embryo.M.N.S received funding from an Early Career Leverhulme Trust fellowship and an Advanced EMBO fellowship. Work in the laboratory of M.Z-G. is funded by the Wellcome Trust (207415/Z/17/Z) and the European Research Council (ERC grant 669198). Work of E.D.S. is funded by NIH grant GM101653

The Blume-Emery-Griffiths neural network: dynamics for arbitrary temperature

The parallel dynamics of the fully connected Blume-Emery-Griffiths neural network model is studied for arbitrary temperature. By employing a probabilistic signal-to-noise approach, a recursive scheme is found determining the time evolution of the distribution of the local fields and, hence, the evolution of the order parameters. A comparison of this approach is made with the generating functional method, allowing to calculate any physical relevant quantity as a function of time. Explicit analytic formula are given in both methods for the first few time steps of the dynamics. Up to the third time step the results are identical. Some arguments are presented why beyond the third time step the results differ for certain values of the model parameters. Furthermore, fixed-point equations are derived in the stationary limit. Numerical simulations confirm our theoretical findings.Comment: 26 pages in Latex, 8 eps figure

Cross-species comparison significantly improves genome-wide prediction of cis-regulatory modules in Drosophila

BACKGROUND: The discovery of cis-regulatory modules in metazoan genomes is crucial for understanding the connection between genes and organism diversity. It is important to quantify how comparative genomics can improve computational detection of such modules. RESULTS: We run the Stubb software on the entire D. melanogaster genome, to obtain predictions of modules involved in segmentation of the embryo. Stubb uses a probabilistic model to score sequences for clustering of transcription factor binding sites, and can exploit multiple species data within the same probabilistic framework. The predictions are evaluated using publicly available gene expression data for thousands of genes, after careful manual annotation. We demonstrate that the use of a second genome (D. pseudoobscura) for cross-species comparison significantly improves the prediction accuracy of Stubb, and is a more sensitive approach than intersecting the results of separate runs over the two genomes. The entire list of predictions is made available online. CONCLUSION: Evolutionary conservation of modules serves as a filter to improve their detection in silico. The future availability of additional fruitfly genomes therefore carries the prospect of highly specific genome-wide predictions using Stubb