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α卫星高阶重复序列傅里叶功率谱中一级和二级周期性级联的层次结构。

Hierarchical structure of cascade of primary and secondary periodicities in Fourier power spectrum of alphoid higher order repeats.

作者信息

Paar Vladimir, Pavin Nenad, Basar Ivan, Rosandić Marija, Gluncić Matko, Paar Nils

机构信息

Faculty of Science, University of Zagreb, Bijenicka 32, Zagreb, Croatia.

出版信息

BMC Bioinformatics. 2008 Nov 3;9:466. doi: 10.1186/1471-2105-9-466.

Abstract

BACKGROUND

Identification of approximate tandem repeats is an important task of broad significance and still remains a challenging problem of computational genomics. Often there is no single best approach to periodicity detection and a combination of different methods may improve the prediction accuracy. Discrete Fourier transform (DFT) has been extensively used to study primary periodicities in DNA sequences. Here we investigate the application of DFT method to identify and study alphoid higher order repeats.

RESULTS

We used method based on DFT with mapping of symbolic into numerical sequence to identify and study alphoid higher order repeats (HOR). For HORs the power spectrum shows equidistant frequency pattern, with characteristic two-level hierarchical organization as signature of HOR. Our case study was the 16 mer HOR tandem in AC017075.8 from human chromosome 7. Very long array of equidistant peaks at multiple frequencies (more than a thousand higher harmonics) is based on fundamental frequency of 16 mer HOR. Pronounced subset of equidistant peaks is based on multiples of the fundamental HOR frequency (multiplication factor n for nmer) and higher harmonics. In general, nmer HOR-pattern contains equidistant secondary periodicity peaks, having a pronounced subset of equidistant primary periodicity peaks. This hierarchical pattern as signature for HOR detection is robust with respect to monomer insertions and deletions, random sequence insertions etc. For a monomeric alphoid sequence only primary periodicity peaks are present. The 1/fbeta- noise and periodicity three pattern are missing from power spectra in alphoid regions, in accordance with expectations.

CONCLUSION

DFT provides a robust detection method for higher order periodicity. Easily recognizable HOR power spectrum is characterized by hierarchical two-level equidistant pattern: higher harmonics of the fundamental HOR-frequency (secondary periodicity) and a subset of pronounced peaks corresponding to constituent monomers (primary periodicity). The number of lower frequency peaks (secondary periodicity) below the frequency of the first primary periodicity peak reveals the size of nmer HOR, i.e., the number n of monomers contained in consensus HOR.

摘要

背景

识别近似串联重复序列是一项具有广泛意义的重要任务,并且仍然是计算基因组学中的一个具有挑战性的问题。通常,对于周期性检测没有单一的最佳方法,不同方法的组合可能会提高预测准确性。离散傅里叶变换(DFT)已被广泛用于研究DNA序列中的主要周期性。在这里,我们研究DFT方法在识别和研究α卫星高阶重复序列中的应用。

结果

我们使用基于DFT的方法,将符号序列映射为数字序列,以识别和研究α卫星高阶重复序列(HOR)。对于HOR,功率谱显示出等距频率模式,具有特征性的两级层次结构作为HOR的特征。我们的案例研究是人类染色体7的AC017075.8中的16聚体HOR串联。基于16聚体HOR的基频,在多个频率上有非常长的等距峰阵列(超过一千个高次谐波)。明显的等距峰子集基于基本HOR频率的倍数(n聚体的乘法因子n)和高次谐波。一般来说,n聚体HOR模式包含等距的次级周期性峰,有明显的等距初级周期性峰子集。这种作为HOR检测特征的层次模式对于单体插入和缺失、随机序列插入等是稳健的。对于单体α卫星序列,仅存在初级周期性峰。符合预期的是,α卫星区域的功率谱中不存在1/fβ噪声和周期性三种模式。

结论

DFT为高阶周期性提供了一种稳健的检测方法。易于识别的HOR功率谱的特征是两级等距层次模式:基本HOR频率的高次谐波(次级周期性)和对应于组成单体的明显峰子集(初级周期性)。低于第一个初级周期性峰频率的低频峰数量(次级周期性)揭示了n聚体HOR的大小,即共有HOR中包含的单体数量n。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85fd/2661002/c7144151ab8e/1471-2105-9-466-1.jpg

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