Fractal landscapes in biological systems: long-range correlations in DNA and interbeat heart intervals

Here we discuss recent advances in applying ideas of fractals and disordered systems to two topics of biological interest, both topics having common the appearance of scale-free phenomena, i.e., correlations that have no characteristic length scale, typically exhibited by physical systems near a critical point and dynamical systems far from equilibrium. (i) DNA nucleotide sequences have traditionally been analyzed using models which incorporate the possibility of short-range nucleotide correlations. We found, instead, a remarkably long-range power law correlation. We found such long-range correlations in intron-containing genes and in non-transcribed regulatory DNA sequences as well as intragenomic DNA, but not in cDNA sequences or intron-less genes. We also found that the myosin heavy chain family gene evolution increases the fractal complexity of the DNA landscapes, consistent with the intron-late hypothesis of gene evolution. (ii) The healthy heartbeat is traditionally thought to be regulated according to the classical principle of homeostasis, whereby physiologic systems operate to reduce variability and achieve an equilibrium-like state. We found, however, that under normal conditions, beat-to-beat fluctuations in heart rate display long-range power law correlations.     

Current-voltage characteristics of double-strand DNA sequences

We use a tight-binding formulation to investigate the transmissivity and the current-voltage (I-V) characteristics of sequences of double-strand DNA molecules. In order to reveal the relevance of the underlying correlations in the nucleotides distribution, we compare the results for the genomic DNA sequence with those of artificial sequences (the long-range correlated Fibonacci and Rudin-Shapiro one) and a random sequence, which is a kind of prototype of a short-range correlated system. The random sequence is presented here with the same first neighbors pair correlations of the human DNA sequence. We found that the long-range character of the correlations is important to the transmissivity spectra, although the I-V curves seem to be mostly influenced by the short-range correlations.     

Nucleotide composition effects on the long-range correlations in human genes

We use the wavelet transform to investigate the fractal scaling properties of coding and noncoding human DNA sequences. We find that the strength of the long-range correlations observed in the introns increases with the guanine-cytosine (GC) content, while coding sequences show no such correlations at any GC content. However, we demonstrate that long-range correlations can be detected when the coding sequences are undersampled by retaining the third base of each codon only. This strongly suggests that the observed correlations are not likely to be due to insertion-deletion mechanisms. We comment about the origin of these correlations in terms of putative dynamical processes that could produce the isochore structure of the human genome. Received: 18 August 1997 / Accepted: 29 October 1997     

Long-range power-law correlations in condensed matter physics and biophysics

We discuss the appearance of long-range power-law correlations in various systems of interest to condensed matter physicists and biophysicists, with emphasis on the recent discovery of long-range correlations in DNA sequences that contain non-coding regions.     

Statistical mechanics in biology: how ubiquitous are long-range correlations?

The purpose of this opening talk is to describe examples of recent progress in applying statistical mechanics to biological systems. We first briefly review several biological systems, and then focus on the fractal features characterized by the long-range correlations found recently in DNA sequences containing non-coding material. We discuss the evidence supporting the finding that for sequences containing only coding regions, there are no long-range correlations. We also discuss the recent finding that the exponent alpha characterizing the long-range correlations increases with evolution, and we discuss two related models, the insertion model and the insertion-deletion model, that may account for the presence of long-range correlations. Finally, we summarize the analysis of long-term data on human heartbeats (up to 10(4) heart beats) that supports the possibility that the successive increments in the cardiac beat-to-beat intervals of healthy subjects display scale-invariant, long-range "anti-correlations" (a tendency to beat faster is balanced by a tendency to beat slower later on). In contrast, for a group of subjects with severe heart disease, long-range correlations vanish. This finding suggests that the classical theory of homeostasis, according to which stable physiological processes seek to maintain "constancy," should be extended to account for this type of dynamical, far from equilibrium, behavior.     

Cantor型人工DNA序列的关联属性及输运性质

对按膨胀规律A→ABA和B→BBB生成的有限长度Cantor型人工DNA序列,采用统计方法研究了序列的净位移及其标准偏差、重标极差函数及其Hurst指数,并将结果与一维随机二元序列进行了对比,直接论证了Cantor序列具有关联、标度不变及自相似等性质.从Anderson紧束缚模型出发,采用重整化群方法研究了该序列的电子输运特性.研究表明具有好的输运效率的扩展态能在较宽的能量区间上存在,随着序列长度的增加,扩展态的能量区间变得更为细碎,但具有好的透射性的电子态数量只是略有减少,共振能态可以在较长的序列中存在 关键词： Cantor型人工DNA序列 关联属性 电荷输运效率 Lyapunov指数     

Statistical Dynamics of Clustering in the Genome Structure

Clustering and long-range correlations in the nucleotide sequences of different categories of organisms are studied. As a result of clustering, the size distribution of coding and non-coding DNA regions is estimated analytically using the Generalised Central Limit Theorem.The alternation of coding regions (which follow a short range size distribution) with non-coding regions (which follow a long range size distribution in higher organisms) leads to DNA structures which have a striking resemblance to random Cantor Fractals. For lower organisms (such as viruses, procaryotes etc.) long-range correlations are sporadically observed and the DNA structures do not present fractality.Statistical models are proposed based on biologically motivated dynamical mechanisms (such as aggregation of oligonucleotides, influx and DNA length reduction), which can account for the above statistical features.     

Long range correlations in DNA: scaling properties and charge transfer efficiency

We address the relation between long-range correlations and charge transfer efficiency in aperiodic artificial or genomic DNA sequences. Coherent charge transfer through the highest occupied molecular orbital states of the guanine nucleotide is studied using the transmission approach, and the focus is on how the sequence-dependent backscattering profile can be inferred from correlations between base pairs.     

Long-range correlations and charge transport properties of DNA sequences

By using Hurst's analysis and transfer approach, the rescaled range functions and Hurst exponents of human chromosome 22 and enterobacteria phage lambda DNA sequences are investigated and the transmission coefficients, Landauer resistances and Lyapunov coefficients of finite segments based on above genomic DNA sequences are calculated. In a comparison with quasiperiodic and random artificial DNA sequences, we find that λ-DNA exhibits anticorrelation behavior characterized by a Hurst exponent 0.5<H<1 while, as far as the segments selected in our Letter are concerned, Ch22 sequence displays a transition from correlation behavior to anticorrelation behavior. The resonant peaks of the transmission coefficient in genomic sequences can survive in longer sequence length than in random sequences but in shorter sequence length than in quasiperiodic sequences. It is shown that the genomic sequences have long-range correlation properties to some extent but the correlations are not strong enough to maintain the scale invariance properties.     

Fractals in DNA sequence analysis

Fractal methods have been successfully used to study many problems in physics,mathematics,engineering,finance,and even in biology,There has been an increasing interest in unravelling the mysteries of DNA;for example,how can we distinguish coding and noncoding sequences,and the problems of classification and evolution relationship of organisms are key problems in bioinformatics,Although much research has been carried out by taking into consideration the long-range correlations in DNA sequences,and the global fractal dimension has been used in these works by other people,the models and methods are somewhat rough and the results are not satisfactory.In recent years,our group has introduced a time series model(statistical point of view)and a visual representation (geometrical point of view) to DNA sequence analysis.We have also used fractal dimension,correlation dimension,the Hurst exponent and the dimension spectrum (multifractal analysis)to discuss problems in this field.In this paper,we introduce these fractal models and methods and the results of DNA sequence analysis.     

Statistical Dynamics of Clustering in the Genome Structure

Clustering and long-range correlations in the nucleotide sequences of different categories of organisms are discussed. Clustering, mostly observed in higher eucaryotes, can be found at different length scales in DNA and Central Limit Theorems are used as links between these length scales. Several dynamical, statistical, mean-field models are proposed based on biologically motivated dynamical mechanisms and they successfully reproduce both the short range behavior observed in coding DNA and the long range, out-of-equilibrium features of non-coding DNA. Such dynamical mechanisms include aggregation of oligonucleotides, influx and DNA length reduction schemes, transpositions, and fusions of large DNA macromolecules. Fractality can be inferred from the short and long range correlations observed in the sequence structure of higher eucaryotes, where the non-coding part is relatively extended. In these organisms the DNA coding/non-coding alternation has the characteristics of finite size, fractal, random sets.     

Statistical and linguistic features of noncoding DNA: A heterogeneous «Complex system»

Summary We present evidence supporting the idea that the DNA sequence in genes containingnoncoding regions is correlated, and that the correlation is remarkably long range-indeed, base pairsthousands of base pairs distant are correlated. We do not find such a long-range correlation in the coding regions of the gene; we utilize this fact to build aCoding Sequence Finder algorithm, which uses statistical ideas to locate the coding regions of an unknown DNA sequence. We resolve the problem of the ?non-stationarity? feature of the sequence of base pairs (that the relative concentration of purines and pyrimidines changes in different regions of the mosaic-like chain) by describing a new algorithm calledDetrended Fluctuation Analysis (DFA). We address the claim of Voss that there is no difference in the statistical properties of coding and noncoding regions of DNA by systematically applying the DFA algorithm, as well as standard FFT analysis, to every DNA sequence (33 301 coding and 29 453 non-coding) in the entire GenBank database. We describe a simple model to account for the presence of long-range power law correlations (and the systematic variation of the scaling exponent α with evolution) which is based upon a generalization of the classic Lévy walk. Finally, we describe briefly some recent work showing that thenoncoding sequences have certain statistical features in common with natural languages. Specifically, we adapt to DNA the Zipf approach to analyzing linguistic texts, and the Shannon approach to quantifying the ?redundancy? of a linguistic text in terms of a measurable entropy function. We suggest that noncoding regions in eukaryotes may display a smaller entropy and larger redundancy than coding regions for plants and invertebrates, further supporting the possibility that noncoding regions of DNA may carry biological information. Paper presented at the I International Conference on Scaling Concepts and Complex Fluids, Copanello, Italy, July 4–8, 1994.     

Experiments to detect long-range heteronuclear shift correlations: LR-J-HSMQC

The utility of the J-HSMQC experiment to detect long-range CH correlations was investigated. Two new long-range J-compensated pulse sequences, LR-J-HSMQC(80,27) and LR-J-HSMQC(27,80), were developed using the (3beta(x))beta(y) composite 90 degrees pulse sequence. These two experiments were shown to be effective for long-range coupling constants, (n)J(CH), that were greater than 3 Hz. Although the overall sensitivities of the long-range J-HSMQC experiments were slightly lower than that of the conventional decoupled HMBC experiment, their 2D maps showed additional cross peaks that could be useful in structure elucidation. LR-J-HSMQC(27,80) was very efficient in yielding two- and four-bond relay correlations. The utility of the new sequences is demonstrated with strychnine as the sample.     

Chaos game representation （CGR）-walk model for DNA sequences

Chaos game representation (CGR) is an iterative mapping technique that processes sequences of units, such as nucleotides in a DNA sequence or amino acids in a protein, in order to determine the coordinates of their positions in a continuous space. This distribution of positions has two features: one is unique, and the other is source sequence that can be recovered from the coordinates so that the distance between positions may serve as a measure of similarity between the corresponding sequences. A CGR-walk model is proposed based on CGR coordinates for the DNA sequences. The CGR coordinates are converted into a time series, and a long-memory ARFIMA (p, d, q) model, where ARFIMA stands for autoregressive fractionally integrated moving average, is introduced into the DNA sequence analysis. This model is applied to simulating real CGR-walk sequence data of ten genomic sequences. Remarkably long-range correlations are uncovered in the data, and the results from these models are reasonably fitted with those from the ARFIMA (p, d, q) model.     

Formation and positioning of nucleosomes: Effect of sequence-dependent long-range correlated structural disorder

The understanding of the long-range correlations (LRC) observed in DNA sequences is still an open and very challenging problem. In this paper, we start reviewing recent results obtained when exploring the scaling properties of eucaryotic, eubacterial and archaeal genomic sequences using the space-scale decomposition provided by the wavelet transform (WT). These results suggest that the existence of LRC up to distances ∼ 20-30kbp is the signature of the nucleosomal structure and dynamics of the chromatin fiber. Actually the LRC are mainly observed in the DNA bending profiles obtained when using some structural coding of the DNA sequences that accounts for the fluctuations of the local double-helix curvature within the nucleosome complex. Because of the approximate planarity of nucleosomal DNA loops, we then study the influence of the LRC structural disorder on the thermodynamical properties of 2D elastic chains submitted locally to mechanical/topological constraint as loops. The equilibrium properties of the one-loop system are derived numerically and analytically in the quite realistic weak-disorder limit. The LRC are shown to favor the spontaneous formation of small loops, the larger the LRC, the smaller the size of the loop. We further investigate the dynamical behavior of such a loop using the mean first passage time (MFPT) formalism. We show that the typical short-time loop dynamics is superdiffusive in the presence of LRC. For displacements larger than the loop size, we use large-deviation theory to derive a LRC-dependent anomalous-diffusion rule that accounts for the lack of disorder self-averaging. Potential biological implications on DNA loops involved in nucleosome positioning and dynamics in eucaryotic chromatin are discussed.     

Efficiency of purging sequences in the long-range heteronuclear shift correlation experiment

The efficiencies of a number of pulse sequences designed to remove directly bonded C-H correlations from long-range C-H shift correlation maps are evaluated. A two-step J filter sequence is shown to give good suppression in 1 D experiments. Its incorporation into the long-range C-H shift correlation experiment with a BIRD sequence at the center of the refocusing period gives the BIRDTRAP sequence, which is shown to yield 2D maps with a few very weak direct correlations and no artifacts. BIRDTRAP has a sensitivity higher than that of FLOCK.     

(De)localization and the mobility edges in a disordered double chain with long-range intrachain correlation and short-range interchain correlation

Correlation effects and phase transitions are central issues in current studies on disordered systems. In this paper, we study the electronic properties of a disordered double chain with long-range intrachain correlation and short-range interchain correlation. Based on detailed numerical calculations, finite size scaling analysis and empirical analytical calculations, we obtain a phase diagram containing rich physics due to the interplay among the disorder, short-range and long-range correlations. Besides the long-range correlation induced localization-delocalization transitions, we find both first-order and second-order quantum phase transitions on changing the short-range correlation. Interestingly, the localization may be suppressed by increasing the disorder strength in some parameter regime and the 'anti-correlation' leads to the most delocalized state. Our studies shine some light on the mechanism of the charge transport in DNA molecules, where both types of correlated disorders are present.     

一维长程关联无序系统中的电子态

利用傅里叶滤波法在一维Anderson无序系统中产生了具有幂律谱密度公式s(q)∝q^-p形式的长程关联随机能量序列，并利用传输矩阵方法计算了系统中引入了长程关联后的局域长度，同时应用负本征值理论对系统中的电子态密度进行了分析，并分别把计算结果与系统中不具有长程关联时的局域长度与电子态密度进行了比较.结果表明，长程幂律关联的引入对电子态的性质产生了很大的影响，当关联指数p≥2.0时，在系统能带中心范围内发生了部分局域态向退局域态的转变，而同时电子态密度也发生了很大的变化，出现了六个范霍夫奇点，系统的能带范围也相应地得到展宽. 关键词： 无序系统 长程关联 局域长度 电子态密度     

Long- and Short-Range Correlations in Genome Organization

We study the size distribution of coding and non-coding regions in DNA sequences. For most organisms we observe that the size distribution P _c(S) of the coding regions of size S shows short range distribution, whereas the size distribution of the non-coding regions follows a power-law decay P _nc(S) S ^{–1 –} , with power exponents indicating clear long-range behavior. We argue, using the Generalized Central Limit Theorem, that the long-range distributions observed in the non-coding are related to the lower level clustering of purines and pyrimidines (1d islands) which follow similar long-range laws. We also address the question of clustering of coding segments in the two complementary strands of DNA. We observe a short-range clustering of coding regions in both strands, expressed by an exponential decay in the clustering size distribution. The decay exponent expresses the degree of short-range correlations and the deviation from random clustering.