Complex network approaches to nonlinear time series analysis

We report the draft genome sequence of the red harvester ant, Pogonomyrmex barbatus. The genome was sequenced using 454 pyrosequencing, and the current assembly and annotation were completed in less than 1 y. Analyses of conserved gene groups (more than 1,200 manually annotated genes to date) suggest a high-quality assembly and annotation comparable to recently sequenced insect genomes using Sanger sequencing. The red harvester ant is a model for studying reproductive division of labor, phenotypic plasticity, and sociogenomics. Although the genome of P. barbatus is similar to other sequenced hymenopterans (Apis mellifera and Nasonia vitripennis) in GC content and compositional organization, and possesses a complete CpG methylation toolkit, its predicted genomic CpG content differs markedly from the other hymenopterans. Gene networks involved in generating key differences between the queen and worker castes (e.g., wings and ovaries) show signatures of increased methylation and suggest that ants and bees may have independently co-opted the same gene regulatory mechanisms for reproductive division of labor. Gene family expansions (e.g., 344 functional odorant receptors) and pseudogene accumulation in chemoreception and P450 genes compared with A. mellifera and N. vitripennis are consistent with major life-history changes during the adaptive radiation of Pogonomyrmex spp., perhaps in parallel with the development of the North American deserts.

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Draft genome of the red harvester ant Pogonomyrmex barbatus

The study of correlation structures of DNA sequences: a critical review.

We discuss examples of complex systems composed of many interacting subsystems. We focus on those systems displaying nontrivial long-range correlations. These include the one-dimensional sequence of base pairs in DNA, the sequence of flight times of the large seabird Wandering Albatross, and the annual fluctuations in the growth rate of business firms. We review formal analogies in the models that describe the observed long-range correlations, and conclude by discussing the possibility that behavior of large numbers of humans (as measured, e.g., by economic indices) might conform to analogs of the scaling laws that have proved useful in describing systems composed of large numbers of inanimate objects.

Anomalous fluctuations in the dynamics of complex systems: from DNA and physiology to econophysics

A segmentation algorithm based on the Jensen-Shannon entropic divergence is used to decompose long-range correlated DNA sequences into statistically significant, compositionally homogeneous patches. By adequately setting the significance level for segmenting the sequence, the underlying power-law distribution of patch lengths can be revealed. Some of the identified DNA domains were uncorrelated, but most of them continued to display long-range correlations even after several steps of recursive segmentation, thus indicating a complex multi-length-scaled structure for the sequence. On the other hand, by separately shuffling each segment, or by randomly rearranging the order in which the different segments occur in the sequence, shuffled sequences preserving the original statistical distribution of patch lengths were generated. Both types of random sequences displayed the same correlation scaling exponents as the original DNA sequence, thus demonstrating that neither the internal structure of patches nor the order in which these are arranged in the sequence is critical; therefore, long-range correlations in nucleotide sequences seem to rely only on the power-law distribution of patch lengths. \textcopyright{} 1996 The American Physical Society.

http://www.biblioteca.uma.es/bbldoc/articulos/16694995.pdf

Compositional segmentation and long-range fractal correlations in DNA sequences

Mutual information function, which is an alternative to correlation function for symbolic sequences, and a "symbolic spectrum" are calculated for a human DNA sequence containing mostly intron segments, those that do not code for proteins. It is observed that the mutual information function of this sequence decays very slowly, and the correlation length is extremely long (at least 800 bases). The symbolic spectrum of the sequence at very low frequencies can be approximated by 1/fα, where f is the frequency and α ranges from 0.5 to 0.85. It is suggested that the existence of the repetitive patterns in the sequence is mainly responsible for the observed long-range correlation. A possible connection between this long-range correlation and those in music notes is also briefly discussed.

https://iopscience.iop.org/article/10.1209/0295-5075/17/7/014/pdf

W. Li

Papers

Long-range correlation and partial 1/fα spectrum in a noncoding DNA sequence