Biomedical subjects

Alain Arneodo

Publications and source records attributed to Alain Arneodo.

6 recordsLinked to original sources

PubMed2005

Replication-associated strand asymmetries in mammalian genomes: toward detection of replication origins.

In the course of evolution, mutations do not affect both strands of genomic DNA equally. This imbalance mainly results from asymmetric DNA mutation and repair processes associated with replication and transcription. In prokaryotes, prevalence of G over C and T over A is frequently observed in the leading strand. The sign of the resulting TA and GC skews changes abruptly when crossing replication-origin and termination sites, producing characteristic step-like transitions. In mammals, transcription-coupled skews have been detected, but so far, no bias has been associated with replication. Here, analysis of intergenic and transcribed regions flanking experimentally identified human replication origins and the corresponding mouse and dog homologous regions demonstrates the existence of compositional strand asymmetries associated with replication. Multiscale analysis of human genome skew profiles reveals numerous transitions that allow us to identify a set of 1,000 putative replication initiation zones. Around these putative origins, the skew profile displays a characteristic jagged pattern also observed in mouse and dog genomes. We therefore propose that in mammalian cells, replication termination sites are randomly distributed between adjacent origins. Taken together, these analyses constitute a step toward genome-wide studies of replication mechanisms.

Animals↗

PubMed2004

Transcription-coupled and splicing-coupled strand asymmetries in eukaryotic genomes.

Under no-strand bias conditions, each genomic DNA strand should present equimolarities of A and T and of G and C. Deviations from these rules are attributed to asymmetric properties intrinsic to DNA mutation-repair processes. In bacteria, strand biases are associated with replication or transcription. In eukaryotes, recent studies demonstrate that human genes present transcription-coupled biases that might reflect transcription-coupled repair processes. Here, we study strand asymmetries in intron sequences of evolutionarily distant eukaryotes, and show that two superimposed intron biases can be distinguished. (i) Biases that are maximum at intron extremities and decrease over large distances to zero values in internal regions, possibly reflecting interactions between pre-mRNA and splicing machinery; these extend over approximately 0.5 kb in mammals and Arabidopsis thaliana, and over 1 kb in Caenorhabditis elegans and Drosophila melanogaster. (ii) Biases that are constant along introns, possibly associated with transcription. Strikingly, in C.elegans, these latter biases extend over intergenic regions that separate co-oriented genes. When appropriately examined, all genomes present transcription-coupled excess of T over A in the coding strand. On the opposite, GC skews are either positive (mammals, plants) or negative (invertebrates). These results suggest that transcription-coupled asymmetries result from mutation-repair mechanisms that differ between vertebrates and invertebrates.

Animals↗

PubMed2004

Generalizing the wavelet-based multifractal formalism to random vector fields: application to three-dimensional turbulence velocity and vorticity data.

We use singular value decomposition techniques to generalize the wavelet transform modulus maxima method to the multifractal analysis of vector-valued random fields. The method is calibrated on synthetic multifractal 2D vector measures and monofractal 3D fractional Brownian vector fields. We report the results of some application to the velocity and vorticity fields issued from 3D isotropic turbulence simulations. This study reveals the existence of an intimate relationship between the singularity spectra of these two vector fields which are found significantly more intermittent than previously estimated from longitudinal and transverse velocity increment statistics.

Journal Article↗

PubMed2004

A practical method to experimentally evaluate the Hausdorff dimension: an alternative phase-transition-based methodology.

We introduce a methodology to estimate numerically the Hausdorff dimension of a geometric set. This practical method has been conceived as a subsequent tool of another context study, associated to our concern to distinguish between various fractal sets. Its conception is natural since it can be related to the original idea involved in the definitions of Hausdorff measure and Hausdorff dimension. It is based on the critical behavior of the measure spectrum functions of the set around its Hausdorff dimension value. We illustrate on several well-known examples, the ability of this method to accurately estimate the Hausdorff dimension. Also, we show how the transition property, exhibited by the quantities used as substitutes of the Hausdorff measure in the corresponding fractal dimension relationships, can be used to accurately estimate the fractal dimension. To show the potential of our method, we also report the results of Hausdorff dimension measurements on some typical examples, compared to a direct application of the scaling relation involved in the box-counting dimension definition.

Journal Article↗

PubMed2003

Three-dimensional wavelet-based multifractal method: the need for revisiting the multifractal description of turbulence dissipation data.

We generalize the wavelet transform modulus maxima (WTMM) method to multifractal analysis of 3D random fields. This method is calibrated on synthetic 3D monofractal fractional Brownian fields and on 3D multifractal singular cascade measures as well as their random function counterpart obtained by fractional integration. Then we apply the 3D WTMM method to the dissipation field issued from 3D isotropic turbulence simulations. We comment on the need to revisit previous box-counting analyses which have failed to estimate correctly the corresponding multifractal spectra because of their intrinsic inability to master nonconservative singular cascade measures.

Journal Article↗

PubMed2002

Long-range correlations between DNA bending sites: relation to the structure and dynamics of nucleosomes.

It has been established that the precise positioning of nucleosomes on genomic DNA can be achieved, at least for a minority of them, through sequence-dependent processes. However, to what extent DNA sequences play a role in the positioning of the major part of nucleosomes is still debated. The aim of the present study is to examine to what extent long-range correlations (LRC) are related to the presence of nucleosomes. Using the wavelet transform technique, we perform a comparative analysis of the DNA text and of the corresponding bending profiles generated with curvature tables based on nucleosome positioning data. The exploration of a number of eukaryotic and bacterial genomes through the optics of the so-called "wavelet transform microscope" reveals a characteristic scale of 100-200 bp that separates two regimes of different LRC. Here, we focus on the existence of LRC in the small-scale regime (10-200 bp) which are actually observed in eukaryotic genomes, in contrast to their absence in eubacterial genomes. Analysis of viral DNA genomes shows that, like their host's genomes, eukaryotic viruses present LRC but eubacterial viruses do not. There is one exception for genomes of poxviruses (Vaccinia and Melamoplus sanguinipes) which do not replicate in the cell nucleus and do not exhibit LRC. No small-scale LRC are detected in the genomes of all examined RNA viruses, with the exception of retroviruses. These results together with the observation of LRC between particular sequence motifs known to participate in the formation of nucleosomes (e.g. AA dinucleotides) strongly suggest that the 10-200 bp LRC are a signature of the sequence-dependence of nucleosome positioning. Finally, we discuss possible interpretations of these LRC in terms of the physical mechanisms that might govern the positioning and the dynamics of the nucleosomes along the DNA chain through cooperative processes.

Bacteria↗